Search Results (198)

Coastal blue carbon ecosystems (traditional types such as mangroves, salt marshes, and seagrass meadows; emerging types such as tidal flats and mariculture) play pivotal roles in capturing and storing atmospheric carbon dioxide. Reliable assessment of the spatial and temporal variation and the carbon storage potential holds immense promise for mitigating climate change. Although previous field surveys and regional assessments have improved the understanding of individual habitats, most studies remain site-specific and short-term; comprehensive, multi-decadal assessments that integrate all major coastal blue carbon systems at the national scale are still scarce for China. In this study, we integrated 30 m Landsat imagery (1992–2022), processed on Google Earth Engine with a random forest classifier; province-specific, literature-derived carbon density data with quantified uncertainty (mean ± standard deviation); and the InVEST model to track coastal China’s mangroves, salt marshes, tidal flats, and mariculture to quantify their associated carbon stocks. Then the GeoDetector was applied to distinguish the natural and anthropogenic drivers of carbon stock change. Results showed rapid and divergent land use change over the past three decades, with mariculture expanded by 44%, becoming the dominant blue carbon land use; whereas tidal flats declined by 39%, mangroves and salt marshes exhibited fluctuating upward trends. National blue carbon stock rose markedly from 74 Mt C in 1992 to 194 Mt C in 2022, with Liaoning, Shandong, and Fujian holding the largest provincial stock; Jiangsu and Guangdong showed higher increasing trends. The Normalized Difference Vegetation Index (NDVI) was the primary driver of spatial variability in carbon stock change (q = 0.63), followed by precipitation and temperature. Synergistic interactions were also detected, e.g., NDVI and precipitation, enhancing the effects beyond those of single factors, which indicates that a wetter climate may boost NDVI’s carbon sequestration. These findings highlight the urgency of strengthening ecological red lines, scaling climate-smart restoration of mangroves and salt marshes, and promoting low-impact mariculture. Our workflow and driver diagnostics provide a transferable template for blue carbon monitoring and evidence-based coastal management frameworks. Full article

This dataset presents environmental observations collected in August 2021 from 18 port and harbor sites located around Jeju Island, Korea. It includes physical, biogeochemical, and greenhouse gas (GHG) variables measured in surface seawater, such as temperature, salinity, dissolved oxygen, nutrients, chlorophyll-a, pH, total alkalinity, and dissolved inorganic carbon. Concentrations and air–sea fluxes of nitrous oxide (N₂O), methane (CH₄), and carbon dioxide (CO₂) were also quantified. All measurements were conducted following standardized analytical protocols, and certified reference materials and duplicate analyses were used to ensure data accuracy. Consequently, the dataset revealed that elevated nutrient accumulation in port and harbor waters and GHG concentrations tended to be higher at sites with stronger land-based influence. During August 2021, most sites functioned as sources of N₂O, CH₄, and CO₂ to the atmosphere. This integrated dataset offers valuable insights into the influence of anthropogenic and hydrological factors on coastal GHG dynamics and provides a foundation for future studies across diverse semi-enclosed marine systems. Full article

Carbon dioxide (CO₂) is a predominant greenhouse gas significantly contributing to atmospheric heat retention, primarily driven by anthropogenic activities intensifying the greenhouse effect. This study aims to evaluate the diversity of plant species, above-ground biomass (AGB), and carbon stock within a dry dipterocarp forest, which is a vital local natural resource. This study presents a comprehensive evaluation of plant species diversity, AGB, and carbon stock capacity within a dry dipterocarp forest at the Nature Study Center, Mahasarakham University, located in the Kham Riang Subdistrict of Kantharawichai District, Maha Sarakham Province, spanning an area of 20.80 hectares. Ten sample plots, each measuring 40 × 40 m, were established and distributed across the study area. The diameter at breast height (DBH) and the height of the trees were meticulously recorded for all trees within these plots. Advanced statistical techniques were employed to calculate the relative dominance (RD), relative frequency (RF), and Importance Value Index (IVI), alongside a comprehensive assessment of plant species diversity. The AGB was assessed using precise allometric equations, with a focus on analyzing carbon storage within woody biomass. The findings revealed the presence of 52 tree species across 26 families within the forest. The total AGB was measured at 144.510 tons, with carbon stock reaching 67.920 tCO₂. These results offer critical insights into enhancing land management strategies to optimize carbon stock, thereby playing a vital role in mitigating greenhouse gas emissions, a significant factor in climate change dynamics. Full article

The ocean is one of the world’s largest anthropogenic carbon dioxide (CO₂) sinks, but closing the carbon budget is logistically difficult and expensive, and uncertainties in carbon fluxes and reservoirs remain. One specific challenge is that measuring the CO₂ flux at the air–sea interface usually requires costly sensors or analyzers (USD > 30,000), which can limit observational capacity. Our group has developed and validated a low-cost ΔpCO₂ system, able to measure both pCO₂^water and pCO₂^air, for USD ~1400 to combat this limitation. The device is equipped with Internet of Things (IoT) capabilities and built around a USD ~100 pCO₂ K30 sensor at its core. Our Sensor for the Exchange of Atmospheric CO₂ with Water (SEACOW) may be placed in an observational network with traditional pCO₂ sensors or ∆pCO₂ sensors to extend the spatial coverage and resolution of monitoring systems. After calibration, the SEACOW reports atmospheric pCO₂ measurements that are within 2–3% of the measurements made with a calibrated LI-COR LI-850. We also demonstrate the SEACOW’s ability to capture diel pCO₂ cycling in seagrass, provide recommendations for SEACOW field deployments, and provide additional technical specifications for the SEACOW and for the K30 itself (e.g., air- and water-side 99.3% response time; 5.7 and 29.6 min, respectively). Full article

Carbon Capture and Storage (CCS) technology presents a practical solution for reducing industrial carbon dioxide (CO₂) emissions through underground anthropogenic CO₂ storage in depleted hydrocarbon reservoirs. The long-term storage efficiency faces several CO₂ leakage challenges that need to be addressed in the planning phase of the CCS project. Thus, effective risk assessment (RA) methodologies are crucial for ensuring safety, regulatory compliance, and public acceptance of CCS projects. This review examines RA parts and their corresponding technical and non-technical challenges. The analysis critically compares over 20 qualitative, semi-quantitative, quantitative, and hybrid RA techniques employed throughout GCS operations. Available quantitative RA tools do not deliver dependable results because they require technical data that become available late in the CCS project development process. Qualitative approaches work well for the initial screening of storage sites with limited data available, yet quantitative methods enable quantification of CO₂ leakage. For the first time, a comparative analysis of two integrated assessment tools is presented in this paper. The techniques achieve success based on high-quality data and analysis of existing technical and non-technical challenges which this paper examines. The comparative analysis outlines the limitations and advantages of every methodology studied and emphasizes the need for integrated hybrid frameworks to boost decision-making in the RA process. Future research should focus on creating or improving existing hybrid frameworks for late-stage RA while utilizing qualitative frameworks in the initial site screening stage to advance GSC’s safe and effective implementation. Full article

Accurate estimation of anthropogenic CO₂ emissions is crucial for effective climate change mitigation policies. This study aims to improve CO₂ emission estimates in China using remote sensing measurements of column-averaged dry air mole fractions of CO₂ (XCO₂) and a neural network approach. We evaluated XCO₂ anomalies derived from three background XCO₂ concentration approaches: CHN (national median), LAT (10-degree latitudinal median), and NE (N-nearest non-emission grids average). We then applied the Generalized Regression Neural Network model, combined with a partition modeling strategy using the K-means clustering algorithm, to estimate CO₂ emissions based on XCO₂ anomalies, net primary productivity, and population data. The results indicate that the NE method either outperformed or was at least comparable to the LAT method, while the CHN method performed the worst. The partition modeling strategy and inclusion of population data effectively improved CO₂ emission estimates. Specifically, increasing the number of partitions from 1 to 30 using the NE method resulted in mean absolute error (MAE) values decreasing from 0.254 to 0.122 gC/m²/day, while incorporating population data led to a decrease in MAE values between 0.036 and 0.269 gC/m²/day for different partitions. The present methods and findings offer critical insights for supporting government policy-making and target-setting. Full article

Carbon dioxide (CO₂) injection into geologic formations has gained global traction, including in South Africa, to mitigate anthropogenic emissions through carbon capture, utilisation, and storage technology. These technological and technical developments require a comprehensive and reliable study of CO₂ sorption equilibria under in situ unmineable coal reservoir conditions. This paper presents novel findings on the study of the equilibrium adsorption of CO₂ on two South African coals measured at four temperatures between 30 and 60 °C and pressures up to 9.0 MPa using the volumetric technique. Additionally, the sorption mechanism and thermodynamic nature of the process were studied by fitting the experimental data into Langmuir–Freundlich (Sips), Tóth, and Dubinin–Astakhov (DA) isotherm models, and the Clausius–Clapeyron equation. The findings indicate that the sorption process is highly exothermic, as presented by a negative temperature effect, with the maximum working capacity estimated to range between 3.46 and 4.16 mmol/g, which is also rank- and maceral composition-dependent, with high-rank vitrinite-rich coal yielding more sorption capacity than low-rank inertinite-rich coal. The experimental data fit well in Sips and Tóth models, confirming their applicability in describing the CO₂ sorption behaviour of the coals under the considered conditions. The isosteric heat of adsorption varied from 7.518 to 37.408 kJ/mol for adsorbate loading ranging from 0.4 to 3.6 mmol/g. Overall, the coals studied demonstrate well-developed sorption properties that characteristically make them viable candidates for CO₂ sequestration applications for environmental sustainability. Full article

The utilisation of fossil fuels has resulted in the continuous increase in anthropogenic carbon dioxide (CO₂) emissions and has led to significant environmental impacts. To this end, the catalytic hydrogenation of captured CO₂ into value-added C1 chemicals has attracted great attention. In this case, significant research efforts have been directed towards the development of heterogeneous catalysts. Owing to the unique properties and functionalities of hydridic hydrogen (H⁻), metal hydrides have shown great promise in hydrogen-involved catalytic processes. This is attributed to their enhanced hydrogen (H₂) absorption-desorption reversibility and newly developed active sites. Nevertheless, their application in the activation and hydrogenation of CO₂ has been overlooked. In this review paper, we provide an overview of recent advances in catalytic CO₂ hydrogenation using metal hydride-based materials. Firstly, the reaction mechanisms of CO₂ hydrogenation toward different C1 products (CO, CH₄, CH₃OH and HCOOH) are introduced to better understand their application trend. Thereafter, we highlight the challenges of developing robust hydride catalysts with different components and structures that enable tuning of their catalytic activity and selectivity. A brief introduction of the CO₂ hydrogenation over typical homogeneous metal hydrides complexes is also presented. Lastly, conclusion, future outlook and perspectives are discussed. Full article

Indoor air pollution is a serious public health issue caused by the accumulation of numerous toxic contaminants within enclosed spaces. Particulate matter (PM_2.5 and PM₁₀), biological contaminants (mould, bacteria, and allergies), inorganic gases (carbon monoxide, carbon dioxide, ozone, and nitrogen dioxide), and a variety of volatile organic compounds (VOCs) are examples of common indoor air pollutants. VOCs are one of the chief indoor contaminants, and their effects on human health have made indoor air quality a serious concern. Indoor VOC concentrations are frequently higher than outdoor levels, according to studies, which raises the danger of exposure, particularly for young people and those with respiratory disorders. VOCs originate from both biogenic and anthropogenic sources, and they can create secondary pollutants like ozone and aerosols, which can lead to cardiovascular and pulmonary problems. Prolonged exposure to VOCs has been associated with respiratory irritation, neurological effects, and an increased risk of chronic diseases. This review examines the primary sources, sampling and analysis approach, and health impact of VOCs in indoor air. Additionally, we compared worldwide regulatory guidelines for VOC exposure limits, emphasizing the need for strict exposure limits to protect human health. Full article

Among the challenges the human population needs to address are threats of global pandemics, increasing socioeconomic inequality, especially in developing countries, and anthropogenic climate change. The latter’s effect has been amplified with the arrival of 2023/24 El Niño, causing an exceptional drought in the Amazon basin, significantly affecting fire conditions and hydroelectric power production in several South American countries, including Ecuador. This study analyzes five criteria pollutants—carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and particulate matter ≤ 2.5 µm (PM_2.5)—during 2019–2024 in Quito, Ecuador, a high-elevation tropical metropolis. Despite long-term efforts to regulate emissions, air pollution levels continue to rise, driven by overlapping crises, including energy shortages, political unrest, and extreme weather events. The persistent failure to improve air quality underscores the vulnerability of developing nations to climate change-induced energy instability and the urgent need for adaptive, diversified, and resilient future energy planning. Without immediate shifts in climate adaptation policies, cities like Quito will continue to experience worsening air quality, with severe implications for public health and environmental sustainability. Full article

Efforts to address anthropogenic climate change have been focused sensibly on mitigation and adaptation. However, given the difficulties in the implementation of a rapid global mitigation process, increasing attention is being given to geoengineering as a way to countervail some of the climate change impacts. This development has increased the private investment in geoengineering research in the last few years, leading to patent filing. The article examines the recent evolution of patents in the emerging field of geoengineering technologies. Despite the secrecy surrounding the field of geoengineering, especially solar radiation management at the state level, patent databases provide transparency, offering technical details, market insights, and information about the key players. Patents, published 18 months after filing, reveal valuable data about geoengineering technologies, the targeted markets, and involved stakeholders. The databases of the International Patent Classification (IPC) and Cooperative Patent Classification (CPC) are used. The focus of the present analysis is on patents in the sub-domains of carbon dioxide removal and solar radiation management and on those held by the large oil producer corporations. The results highlight the patents filed in the controversial area of SRM. The growing economic significance of geoengineering requires the protection of innovations through patents coupled with the implementation of a global governance system based on climate justice and ethical responsibility. Full article

The “top-down” global stocktake (GST) requires the processing of vast volumes of hyperspectral data to derive emission information, placing greater demands on data processing efficiency. Deep learning, leveraging its strengths in the automated and rapid analysis of image datasets, holds significant potential to enhance the efficiency and effectiveness of data processing in the GST. This paper develops a method for detecting carbon dioxide (CO₂) emission hotspots using a convolutional neural network (CNN) with short-lived and co-emitted nitrogen dioxide (NO₂) as a proxy. To address the data gaps in model parameter training, we constructed a dataset comprising over 210,000 samples of NO₂ plumes and emissions based on atmospheric dispersion models. The trained model performed well on the test set, with most samples achieving an identification accuracy above 80% and more than half exceeding 94%. The trained model was also applied to the NO₂ column data from the TROPOspheric Monitoring Instrument (TROPOMI) for hotspot detection, and the detections were compared with the MEIC inventory. The results demonstrate that in high-emission areas, the proposed method successfully identifies emission hotspots with an average accuracy of over 80%, showing a high degree of consistency with the emission inventory. In areas with multiple observations from TROPOMI, we observed a high degree of consistency between high NO₂ emission areas and high CO₂ emission areas from the Global Open-Source Data Inventory for Anthropogenic CO₂ (ODIAC), indicating that high NO₂ emission hotspots can also indicate CO₂ emission hotspots. In the future, as hyperspectral and high spatial resolution remote sensing data for CO₂ and NO₂ continue to grow, our methods will play an increasingly important role in global data preprocessing and global emission estimation. Full article

The accurate quantification of anthropogenic carbon dioxide (CO₂) emissions in urban areas is hindered by high uncertainties in emission inventories. We assessed the spatial distributions of three anthropogenic CO₂ emission inventories in Shanghai, China—MEIC (0.25° × 0.25°), ODIAC (1 km × 1 km), and a local inventory (LOCAL) (4 km × 4 km)—and compared simulated CO₂ column concentrations (XCO₂) from WRF-CMAQ against OCO-3 satellite Snapshot Mode XCO₂ observations. Emissions differ by up to a factor of 2.6 among the inventories. ODIAC shows the highest emissions, particularly in densely populated areas, reaching 4.6 and 8.5 times for MEIC and LOCAL in the central area, respectively. Emission hotspots of ODIAC and MEIC are the city center, while those of LOCAL are point sources. Overall, by comparing the simulated XCO₂ values driven by three emission inventories and the WRF-CMAQ model with OCO-3 satellite XCO₂ observations, LOCAL demonstrates the highest accuracy with slight underestimation, whereas ODIAC overestimates the most. Regionally, ODIAC performs better in densely populated areas but overestimates by around 0.22 kt/d/km² in relatively sparsely populated districts. LOCAL underestimates by 0.39 kt/d/km² in the center area but is relatively accurate near point sources. Moreover, MEIC’s coarse resolution causes substantial regional errors. These findings provide critical insights into spatial variability and precision errors in emission inventories, which are essential for improving urban carbon inversion. Full article

The significant anthropogenic carbon dioxide (CO₂) emissions from cement production and the disposal of the majority of post-consumer waste glass into landfill sites have increased environmental pollution. In order to reduce the environmental impact, ground glass pozzolan (GGP) as a partial cement replacement has drawn interest from the concrete industry. This review examines the potential of GGP as a supplementary cementitious material (SCM), exploring the chemical composition of pozzolans, the different types of glass used for GGP, and the impact of glass color on pozzolanic reactivity. In addition, this study gathers the most recent research articles on the fresh and mechanical properties of concrete incorporating GGP. Key findings show that the incorporation of GGP in concrete improves the modulus of elasticity and the compressive, tensile, flexural, and punching strengths due to the pozzolanic reactions. The results indicate that GGP, made from waste glass, has pozzolanic properties that form additional strength-enhancing calcium silicate hydrate (C-S-H) gel and densify the concrete matrix. Additionally, the life cycle assessments of GGP-incorporated concrete demonstrate reductions in energy consumption and CO₂ emissions compared to conventional concrete, supporting a circular economy and sustainable construction practices. Full article

An important issue in the sustainable development of agricultural engineering today is the use of biogas plants for the production of electricity and heat from the organic waste of agricultural products and other low-quality products, which also contributes to the improvement of environmental safety. Traditional methods for assessing the apparent severity of the Roslynnytsia campaign based on statistics from the dominions proved to be ineffective. A hypothesis was proposed regarding the possibility of estimating the apparent biomass by averaging the indicators of depletion and assessing the CH₄ and CO emissions based on satellite monitoring data. The aim of this work is to create a methodology for preparing a raw material base in united territorial communities to provide them with electrical and thermal energy using biogas plants. The achievement of this goal was based on solving the following tasks: monitoring biomethane emissions in the atmosphere as a result of rotting organic waste, and monitoring carbon monoxide emissions as a result of burning agricultural waste. Experimental studies were conducted using earth satellites on sites with geometric centers in the village of Gaishin in the Pereyaslav united territorial community, the city of Ovruch in the Zhytomyr region, the Oleshkovsky Sands National Park in the Kherson region (Ukraine), and the city of Jüterbog, which is located in the state of Brandenburg and is part of the Teltow-Fläming district (Germany). The most significant results of this research involve the methodology for the preparation of the raw material base in the united territorial communities for the production of biogas, based on indirect measurements of methane and carbon dioxide emissions using the process of remote sensing. Based on the use of the proposed scientific and methodological apparatus, it was found that the location of the territory with the center in the village of Gaishin has better prospects for collecting plant raw materials for biogas production than the location of the territorial district with the center in the city of Ovruch, the emissions in which are significantly lower. From March 2020–August 2023, a higher CO concentration was recorded on average by 0.0009 mol/m², which is explained precisely by crop growing practices. In addition, as a result of the conducted studies, for the considered emissions of methane and carbon monoxide for monitoring promising raw materials, carbon monoxide has the best prospects, since methane emissions can also be caused by anthropogenic factors. Thus, in the desert (Oleshkivskie Pisky), large methane emissions were recorded throughout the year which could not be explained by crop growing practices or the livestock industry. Full article